“Biology has gone digital. Time to learn about it.”
This is episode 7 of The French Tech Comedy, Season 2
Episode 6: The Methylation of Money
Previously in The French Tech Comedy: In Season 2 of The French Tech Comedy, we follow characters like Japanese oncologist and bioinformatics engineer Takafumi Nagato, who is leading the lab of Bioinformatics for personalised CAR-T-therapies in a Tokyo clinic, and his patient, Chinese giant TenBa’s founder Ken Ba, a zillionaire from Shanghai. Yuki, Taka’s sister, is a French-speaking geisha, meaning “artist” in Japanese, in touch with the French Tech. She just got married to a French engineer who was working in Taka’s lab, Nono, and has secretly donated her healthy T-cells to Taka’s patient who, after his second cancer relapse, decided to try an innovative treatment called “liquid biopsy”. Indeed, Ba is becoming an expert in genomic precision medicine. In his case it is a matter of life or death. Among Yuki’s friends in the French Tech branch is Frederic Mougin, a biologist, founder of the startup Gene-i-us:
“We are developing a patient-centric tool for patients to collect, share & monetize their medical, genomics, lifestyle, IoT data with academics & pharma industry.”
Yuki had promised she would introduce Mougin to people working with Facebook Singapore; among them: Nono. What biz plan can Gene-i-usimplement, in order to work with Facebook? Mougin is using a lot of buzz words, but when it turns out Ba’s cancer mutation has entered the stock exchange market, thanks to the efforts of a pharmaceutical company, his oncologist, Taka, fears a Ba Gate. More than ever, the privacy of genetic data is instrumental in the process of developing precision medicine. Singapore is the Chinese Mecca of I.P. and patents. A cryptocurrency, that is seen by financial specialists as a security, is used as a way to reward (healthy and sick) patients in exchange of their DNA data. Yuki is wondering if this kind of money will revolutionise the whole financial and pharmaceutical market as we know it, or will all digital currencies end up behaving like any other tradable financial asset? After all, a security is a tradable financial asset. Ba, Taka’s cancer patient, is trying to gain insight into the situation… While spending a few days in Malaysia both for business and vacation, TenBa’s founder gets to meet with a total stranger who in fact he only knows too well: Simone, Malaysian Chinese actress Michelle Yeoh’s niece. Between Ba and Simone, things are complicated. But it is only the beginning… Simone is trying to make an algorithmic cryptocurrency that could mimmic biological processes within the human body. Meanwhile, Manga artist Koba writes about the blurring frontier between curing and enhancing in the genomic precision medicine era, and the consequences in society. At school, Simone needs to present her Science Fair project alone…
— — — — — — — — — — —
Overanxious auntie Michelle had bribed a student from Simone’s class. She wanted her niece’s science fair presentation to be filmed, live. A few days later, she sent a link to a video to a friend of hers, Chinese giant TenBa’s founder Ken Ba, a zillionaire from Shanghai. She’d compiled a 10 minutes extract for him to see, and a question:
“ — What do you think?”
Ba played the video again. The Q&A session caught his attention. Simone was answering the teacher’s questions with questions of her own, and obviously, the student was asking the right questions. And as the teacher was unable to answer them, she was trying to do the job.
Simone: “ — My question for you is about the technical options regarding digital health and medicine. My genome or my DNA data on my mobile phone. What is the science behind it? Your DNA & medical data on your smartphone. Browse it on iTunes, own it & monetise it. In China, technical options have been reviewed, choices have been made already. As I am not sure if this is the case in Europe and in the US, I would like to present you with the options that are available.
One technical choice is the offline storage of patients’ DNA variants, no private cloud required, and in order to exchange data and monetise on the patient’s side, the blockchain will be used: a blockchain layer can add cryptology and traceability to a data packet. The user sends his data to the outside, it encrypts automatically and adds a tracer, it is blockchain technology. His data is protected when leaving home, and the app client is able to make sure that the data have arrived and will be used for approved purposes, and if a payment is made, traceability is attached to the transaction. The function of decentralisation that is achieved by the blockchain technology is managed via specific and various keys. Now, my question is about those keys.”
Teacher: “ — What keys?”
Simone: “ — Protect your genome by storing it in a cloud? why not store it at home rather, disconnected, that’s a good protection. The technology of some platforms will allow you to do that. Then, when you need to share your data with health professionals (those able to use it), or with academic or university hospitals, with the pharmaceutical industry to get medical advice or monetise your data, as it can be worth up to $ 20,000 and more, a Blockchain technology is added to ensure traceability and payment. All done by a platform.
It can be guessed that China (iCarbonX & Tencent) and probably Amazon and Apple are heading towards more expensive technical solutions … We have to store the complete genome and all the annotations relating to it. When you read about genome storage, you need to know that the amount of data coming out of the sequencing machines can go beyond 120 GB. But honestly, what we need, the sequence of our genome, and the list of differences from the reference human genome, is less than 5GB. When using a service such as 23andMe or similar, the storage space needed is 20MB. A genomic tumour profile, less than 5MB.
Technical solutions chosen by China might be data that are being stored in encrypted mode in a private cloud, with encryption and decryption keys for storage and transit that are multiple, and shared by different actors of the business model, including the patient.
This obviously will be way more costly than the alternative as proposed by other platforms, I mean, the offline storage solution I was referring to earlier, but Tencent can afford it … The argument is to say that in some cases, such as breast cancer and cystic fibrosis, some proven and known genetic mutations give the disease. The famous variants. The low hanging fruit in direct to consumer genetics. Where a handful of variants are responsible for a disease or a given phenotype, the offline storage model seems very useful. Less is more. For the future, however, as the research seems to be moving towards a complete sequencing of the genome, because of the so-called epigenetics control levers, which we hardly know a thing about today … For many diseases, and their prevention, knowing about just a handful of mutations might not be good enough… In most cases, there might be more triggering factors, spread over the entire genome, the equivalent of the map of the world. But we are still very far from knowing, deciphering and interpreting all the DNA data of everyone — the individual genome.”
“ — I’m sure the rest of the class is as confused as I am about the blockchain buzz. That Bitcoin thing. Would you care to elaborate a little bit more on that?”
“ — Blockchain is just a data security and traceability technology that genomics will benefit from. Do not confuse Blockchain with crypto-currencies, something that the general public often does. Crypto-currencies use Blockchain.”
Somebody in the class had a question:
“ — But anonymisation of DNA data, I mean, really? Is this a thing? American geneticists claim the opposite. Genetic and anonymous seem rather antinomic.”
Simone: “ — Genomic data as published on open-access websites are simply unidentified, and indeed MIT has shown that we can go back to individuals and their addresses anyway. Some patents extract the unique parts of our genome and encrypt them in a key that no longer allows to return to the complete genomic data, in order to be able to use our genomic data in public applications, without revealing ourselves genetically.”
Soon, another student in the class explained what the blockchain was, in the context of direct-to-consumer genetics.
“ — Simone is right. For the sequencing of a complete genome and all that we can do with it, it will take private clouds, encrypted data, encryption and decryption keys, distinct and multiple, in addition to the blockchain, which in this system plays the role of the sealed envelope. In direct-to-consumer genetics, think of the blockchain as a notary of some kind.”
“ — The blockchain as a notary. Now that’s an interesting point of view…”
The teacher wasn’t sounding too thrilled about discussing the notion of DTC genetics with the blockchain and the privacy of data, though. What her students needed to learn before the upcoming exam was about organs and chemistry and physics; she had not anticipated that such a passionate debate would flare up. Now, the students were talking about some Japanese mangas dealing with what she simply called the medicine of the future. Instead of surgical procedures, the students were debating the role of blockchain and computer coding in Python and R-Stats in molecular biology. Something she wasn’t prepared to discuss. She couldn’t even write computer code in Python or R-stats language. Obviously, some of the students were learning about it in private lessons, paid by their parents. And they were boasting about it:
“ — Medicine is not about organs anymore. No need to dissect frogs; we will be dissecting the genome with CRISPR.”
Simone was now debating with a fellow student. Others were asking for explanations. Before the teacher knew it, a student concluded about Simone’s presentation. Wait. Wasn’t she supposed to do that part? She was still the class teacher, right? But for now, she was being assaulted by buzz words, with no reality at all, coming from social networks. Instagram, WeChat, WhatsApp, Line, Facebook, Twitter… CRISPR, dissecting the DNA, app clients selling their DNA data, browsing their genome on iTunes… Apparently, she was living in one world, and her students in another one. Two different worlds, with either no overlaps at all, or only very limited overlaps, like, for example, the exams.
“ — The take-home message in Simone’s presentation: if we want to start with actionable processes that will make the real science in direct-to-consumer genetics survive and thrive — as we are still far from deciphering the complete DNA, at least today — the less-is-more biz model seems to fit in. No need of online storage. No private cloud, in fact, no cloud at all. But if you look at the business model that both Carenity and PatientsLikeMe have in the US, you see that the de-identified data are collected and monetised by those companies, but patients don’t own their data and don’t share the revenues, they are not part of the monetisation process. What we need instead, according to Simone, is a platform that does not access patient data, and associates it with revenue when monetisation exists, in a data exchange process that occurs directly between patients and the data buyer.”
“ — Exactly. Thank you Fred.”
Simone’s face was beaming.
Somebody else in the class wanted to say something.
“ — I am of European origin. I am not sure what the European market will decide. Will the expensive and complex technical solution be implemented by a European player? Will we get started with a business model that is fair, simple and modest — still a better alternative than losing the battle of data privacy altogether and handing over to US or Chinese consortiums and governments our private data…”
“ — What will be the options in Singapore? What business model do we want for our DNA data privacy?”
“ — OK, OK,” said the teacher:
“ — Thank you everyone. Time for peer evaluation. What part of the presentation did you like best? … Yes, Juan, go ahead.”
“ — When she said: Judging by how things are going, I think I will manage my own health in a private cloud, in predictive mode, as designed and implemented by a made-by-China iCarbonX/Tencent, or by one of the GAFAM companies. It will be a Netflix biz model, and it will cost me US $10 per month.”
“ — OK. Who agrees?”
Many were raising their hands.
“ — Now what is your point of view, Daniel?”
“ — I am concerned about protecting our sovereignty, when it comes to dealing with the genetic data of people. Personally, I would go for the less-is-more option. No storage in the cloud at this point, as I do not wish to hand over my data privacy to US or China governments. Also, what Rachel meant when she said she is of European origin: I think she would like to avoid the technological sinking of Europe in terms of genetic data — the privacy issue — , which of course are linked to national security.”
Two nerds were joking about what had just been said:
“ — Yeah but if you want to receive the CRISPR-updates that are tailored to your genome, made and sent via Desktop Genetics, or iCarbonX, or Oxford Nanopore, or Alibababu Genetics, then your genome will have to be online. So the technology behind your less-is-more platform will have to evolve accordingly, even if off-line storage of data is good for starters, I’ll grant you that.”
“ — Haha. Patricia will order those cat claws that she’s been dreaming about for years, right?”
“ — And my li’l sist’ will want a unicorn for Christmas.”
“ — I’d date any girl who successfully re-engineers herself with cat claws and a unicorn’s head.”
“ — Haha.”
“ — OK, OK, we appreciate your hint of humour on the off-line storage model of DNA data. So what we just learned today is that blockchain is just a data security and traceability technology that genomics will benefit from. Do not confuse Blockchain with crypto-currencies, something that the general public often does. Crypto-currencies use Blockchain. So does genomic precision medicine, or the future of medicine, in the context of the upcoming direct-to-consumer genetics.”
“ — Madam, it’s not the future of medicine. It’s happening now.”
“ — What’s just around the corner is the exam about HLA genotyping for kidney transplantation. In just two weeks, think about it. Then that’ll be a wrap for Q3, and, come to think about it, even for the whole semester. I’m merely trying to discuss facts here, we’re not living in the virtual world of buzz words, like it or not.”
“ — But Madam, can we at least talk about the xenotransplant experiments that are using CRISPR, in China and in the US?”
“ — Oh, you mean those human organs that they are trying to breed in pigs?”
“ — I didn’t know they were using CRISPR for that.”
“ — Also, we could be discussing the upcoming tokenisation of healthcare?”
“ — Don’t you think we’ve heard enough buzz words for today already?”
Rachel, the student with European roots, was raising her hand again.
“ — I think Germaine is right. So…”
Justin, her neighbour, interrupted.
“ — What do you think, Madam? Do you think they should start in Europe right away with the expensive and ambitious solutions — store the complete genome and all annotations in encrypted mode in a private cloud, with encryption and decryption keys for storage and transit that are distinct and multiple? Or should they turn to some kind of low-hanging fruit, a more convenient and inexpensive model that would allow them to get started right away? And how about us here in Singapore? Will the government interfere? Will there be new laws?”
Ba couldn’t believe his ears. The debate was going on. The students were brilliant and passionate. But the teacher was obviously overwhelmed and annoyed.
Justin and Rachel were now examining the data privacy issue and the technical options in the light of a projected BRCA1 / 2 (breast cancer) scenario:
“ — It could be a way to access genomic data for free, while monetising your own data for income.”
“ — Wait. The phenotype data is the lifestyle and all data related to the individual’s physiology, including a diagnosis made by an oncologist. The genotype data is the result of DNA sequencing tests for an individual, correct?”, said Justin.
“ — Correct,” said Rachel.
“ — So now, that part with your biz plan. How will you implement it?,” asked Justin. Rachel answered:
“ — Imagine. You have a startup, you are trying to create a DTC genetics platform, ok? You have a new biz model for your app clients. Or patients. Or whatever. To women who already have phenotype data, and who want to sell their data through our platform — the pharmaceutical industries might be willing to pay more than $10,000 for phenotype and genotype data — you will offer a genetic test, and together, your app clients and yourself, you will sell the data and share the revenue. For women who already have the phenotype + genotype data, you will share 50/50, and for those who only have the phenotype, you will offer a genetic test and you will share the income, 70/30.”
The whole class was listening. Everybody was working on the biz plan, and Simone was taking notes on the class’ whiteboard, for everybody to see.
“ — My mom’s an oncologist, I mean, a physician, dealing with cancer patients” said Rachel:
“ — With an economic model of data monetisation revenue sharing, she says it is possible to consider free distribution of this type of testing. Let me explain something: the BRCA1 / 2 data per se are not worth much. Lifestyle data, family history data, treatment data, combined with BRCA1 / 2 data, are of great scientific AND economic value, likely over US $10,000 per dataset, on the pharmaceutical market. Now, about the patients who collect lifestyle data, family history data, medical treatment data and who are ready to monetise them via a platform: if your startup can sell the data to the pharmaceutical industry for US $ 10,000 provided you add one BRCA1 / 2 test, and share income 50/50, then you should be able to sponsor the BRCA1 / 2 test to the women who do not have one. A way to access genomic data for free, while monetising your own data for income. Brilliant, right?”
“ — Your mom has a startup?”
“ — Kids, let’s not…”
The teacher got interrupted.
Justin was talking again: “ — Should the A.I. actually take the power, the value of the data will be much greater than that of the test itself, therefore, I can give a test to the patient for free and then team up with the patient to resell the whole phenotype-genotype data to the AI and companies that need the data for their business.”
“ — That’s already the case,” says my mom. Rachel continued:
“ — The value of the data is greater than that of the test itself, that is to say that a genome is worth less than 600 US dollars today (in China). Remember the US $ 20,000 Genotype that 23andMe sold to Genentech in 2014?”
She paused, then:
“ — Personally, I’m planning on having my genome sequenced — and medical interpretation — and I would like to see in Europe a minimally invasive medicine system, enabling the patients to store and share and monetise their medical and DNA data. But maybe it’ll happen in China or in the US before it happens anywhere else in the world, what do you think?”
This was the final segment of the video sent by Michelle. So, this was Simone’s science fair project in school. Wow. Ba was lapping it up.
“ — Dear Michelle,
Thank you so much for the video. I found it so interesting. I will be in Malaysia again next week-end. Let’s discuss this over a dish of handmade pasta. They say Maiale’s framboisier and strawberry shortcake are the best in town. I am already torn and agonising over the choice and need your help, as you might imagine. Looking forward,
Ba.”
In Ba’s mind, the words from the video were still echoing.
“ — Judging by how things are going, I think I will manage my own health in a private cloud, in predictive mode, as designed and implemented by a made-by-China iCarbonX/Tencent, or by one of the GAFAM (*) companies. It will be a Netflix biz model, and it will cost me US $10 per month. Biology and IT have merged. Time to learn about it.”
Biology and IT have merged. Time to learn about it. Was it Simone or Rachelle who had said this? Rachelle’s mom, maybe? In any case, it was quite accurate.But the teacher looked very skeptical. She was neither impressed, nor pleased.
(*) GAFAM: Google-Apple-Facebook-Amazon-Microsoft
The equivalent of GAFAM in China would be BATX: Baidu-Alibaba-Tencent-Xiaomi
Catherine Coste
MITx 7.00x, 7.QBWx, 7.28x1–2 certified
Teacher and Member of the Walking Gallery of Health Care, founded by US activist Regina Holliday
Table of Contents:
Episode 1 of Season 2: Your DNA Will See (and Mutate) Your Credit Card Now
Episode 2 of Season 2: The Bitcoin That Pulled the Double Helix Apart
Episode 3 of Season 2: Kabuki Theatre and Desktop Epigenetics
Episode 4 of Season 2: Tenjin and TenGene
Episode 5 of Season 2: TenGene, Gene-i-us and a thousand planets in between
Episode 6 of Season 2: The Re:Creators Fault Line and the Epigenetic of Worldwide Middle Class
For Season 1 of The French Tech Comedy (all episodes), see here.
